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Cognitive Exoskeleton MCP Server

Cognitive Exoskeleton MCP Server

by hanjiang-215
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

ingest_note

Extract knowledge entities and relationships from any note or text, store them in your personal knowledge graph for a dynamic view of your ideas.

Instructions

Extract knowledge entities and relationships from a note or text, and store them in the personal knowledge graph. Accepts either raw text content or a file path to a Markdown/text file.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ingest_note"
  }
}

Input Schema

NameRequiredDescriptionDefault
contentNoRaw text content to extract knowledge from. Provide this OR file_path.
file_pathNoPath to a Markdown or text file to read and extract from. Provide this OR content.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the write operation ('store') and input constraints, but omits side-effect details such as whether existing entities are overwritten, idempotency, or permissions. It also doesn't mention what happens if both content and file_path are provided.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no redundancy: the first states the core purpose, the second clarifies input flexibility. Density is high and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations and no output schema, the description should mention the return value or success indication. It explains the main purpose and input well, but leaves out expected output and error/edge-case behavior, leaving some gaps for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for both parameters, and the descriptions in the schema already convey the OR relationship. The tool description adds no new meaning beyond a brief restatement of the input options, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the action ('Extract knowledge entities and relationships') and the resource ('personal knowledge graph'), distinguishing it clearly from sibling tools that query or analyze. The verb+resource structure is precise and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for ingesting notes into the knowledge graph and clearly notes the two accepted input modes. It doesn't explicitly contrast with sibling tools or state when not to use this tool, but the context is strong enough for a competent agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

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